upload README and requirement

README.md

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-license: cdla-sharing-1.0
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+# Classification of Sugarcane Leaf Disease
+
+## Model Description
+The model is based on EfficientNet architecture and has been fine-tuned on a balanced dataset containing six classes:
+
+- **Bacterial Blight Disease**
+- **Healthy Leaves**
+- **Mosaic Disease**
+- **Red Rot Disease**
+- **Rust Disease**
+- **Yellow Disease**
+
+The model accepts RGB images of sugarcane leaves and outputs the predicted disease class.
+
+## Dataset
+The dataset used for training consists of **19926 images** of sugarcane leaves, evenly distributed across the six disease classes. Each image has been pre-processed and augmented to improve model performance.
+
+### Data Augmentation Techniques Used:
+
+- Random rotation
+- Flipping
+- Zooming
+- Resizing
+- Cropping
+
+## Model Evaluation
+Epoch [10/10], Loss: 0.2903, Accuracy: 90.28%
+Validation Loss: 0.3633, Accuracy: 86.32%
+
+Accuracy_test: 0.8683
+
+## Acknowledgements
+The dataset used for training can be found : https://www.kaggle.com/datasets/akilesh253/sugarcane-plant-diseases-dataset
+
+## License : CDLA-Sharing-1.0

requirement.txt

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+torch==2.0.0
+torchvision==0.15.0
+pandas==1.5.3
+numpy==1.24.2
+matplotlib==3.7.1
+Pillow==9.2.0
+scikit-learn==1.2.0